MRI RAPID: ACQUISITION OF A FIELD SPECTROSCOPY ENVIRONMENTAL ANALYSIS SYSTEM FOR GULF OIL SPILL RESEARCH

此次授予MRI-RAPID是为了应对英国石油公司（BP）位于路易斯安那州海岸外的墨西哥湾深水地平线石油钻井平台发生爆炸后的事件。该提案的目的是获得一个现场光谱环境分析系统，以便收集深水地平线漏油事故的高度易腐数据。更具体地说，该仪器将用于在350 nm至2500 nm的应力范围内对溢油和植被的光谱响应进行现场测量。由于泄漏石油的空间分布和物理化学成分在与环境和石油收集工作相互作用时迅速演变，因此迫切需要收集这些现场样品。这种大规模灾难的短暂性和动态性要求我们在数据收集、基准和定量分析方面立即和持续努力，以监测、评估和管理这次和未来泄漏的影响。新仪器将使该团队能够在不同地点（如深水、浅水、沼泽和海滩）对各种物理形式的溢油（如光泽、斑块、焦油球）的太阳反射率进行时间敏感的现场测量，同时记录其地理空间位置。结合卫星和/或飞机获取的高光谱图像，该团队将能够进行潜在的变革性研究：1)寻求光谱空间解决方案，以在开阔水域实现更精确的石油分布图；2)根据其谱和水体条件估算浮油厚度；3)利用光谱分解技术评估陆上焦油球的数量，以支持清理活动；4)在复杂的、环境敏感的生态系统中检测石油的存在。团队中的环境毒理学家将使用该仪器对受原油胁迫的生态系统进行光谱分析。该仪器的获得将显著增强德克萨斯理工大学计算机视觉和图像分析实验室（CVIAL）的能力，使研究生和本科生能够在成像光谱和高光谱遥感方面获得实践研究经验，并广泛应用于灾害响应、环境监测和国防。

This MRI-RAPID award is in response to events subsequent to an explosion on the British Petroleum (BP) Deepwater Horizon Oil Rig in the Gulf of Mexico off the coast of Louisiana. The objective of this proposal is to acquire a Field Spectroscopy Environmental Analysis System to enable collection of highly perishable data on the Deepwater Horizon oil spill. More specifically, the instrument will be used to take in-situ measurements of the spectral response of oil spill and vegetation under stress between 350 nm and 2500 nm. The need for collecting these field samples is urgent due to the rapid evolution of spatial distribution and physical-chemical composition of leaked oil as it begins interacting with the environment and oil collection efforts. The transient and dynamic nature of such a large-scale disaster calls for both immediate and continuous efforts in data collection, benchmarking, and quantitative analysis for monitoring, assessment, and management of the impact of this and future spills. The new instrument will enable the team to take time-sensitive, in-situ measurements of solar reflectance of oil spill in various physical forms (e.g. sheen, patch, tar balls) at various sites (e.g. deep water, shallow water, marshes, and beaches) while recording their geospatial locations. In conjunction with hyperspectral images acquired by satellites and/or aircraft, the team will be able to pursue potentially transformative research in 1) seeking a spectral-spatial solution for achieving more accurate oil distribution mapping in open water; 2) estimating oil slick thickness based on its spectrum and water conditions; 3) assessing the quantity of tar balls onshore using spectral un-mixing to support clean-up activities; and 4) detecting the presence of oil in complex, environmentally sensitive ecosystems. Environmental toxicologists on the team will use the instrument to perform spectral analysis of ecosystems stressed by crude oil. The acquisition of this instrument will significantly enhance the capabilities of the Computer Vision and Image Analysis Laboratory (CVIAL) at Texas Tech University to enable hands-on research experience for graduate and undergraduate students in imaging spectroscopy and hyperspectral remote sensing with broad applications in disaster response, environmental monitoring, and national defense.